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Record W4405540573 · doi:10.1503/cjs.011624

Does the type of biomesh influence recurrence in abdominal wall reconstruction? A long-term follow-up to a randomized controlled trial

2024· article· en· W4405540573 on OpenAlexaffvenue
Jaiden Punia, Chad G. Ball, Andrew W. Kirkpatrick, Thomas W. Clements

Bibliographic record

VenueCanadian Journal of Surgery · 2024
Typearticle
Languageen
FieldMedicine
TopicHernia repair and management
Canadian institutionsMerck Canada Inc. (Canada)
Fundersnot available
KeywordsMedicineTerm (time)Randomized controlled trialSurgeryGeneral surgery

Abstract

fetched live from OpenAlex

This discussion describes the long-term follow-up of a prospective randomized controlled trial evaluating the performance of the 2 most common biomesh products utilized in the context of complex abdominal wall reconstructions. Although the incidence of hernia recurrence increased over time to 26% (median follow-up 62 mo), both biomesh products performed similarly. Biomesh product choice should remain cost-conscious.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.025
metaresearch head score (Gemma)0.045
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.045
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.012
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0030.004
Open science0.0020.001
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0080.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.025
GPT teacher head0.286
Teacher spread0.261 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2024
Admission routes2
Has abstractyes

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